4 Problems

A New Generation of Retail Tech Startups is Redefining the Industry with AI

AI Bridges the Consumer-Product Language Gap

The disconnect between how retailers describe products and how consumers search for them represents a multibillion-dollar problem in lost sales and missed opportunities. This gap is particularly acute as shopping becomes more fragmented across channels, from marketplaces to social media to traditional e-commerce sites. Two companies are taking distinctly different approaches to solving this challenge.

Lily AI addresses what founder Purva Gupta calls "the missing consumer narrative." After interviewing over 1,000 women about their shopping motivations, Gupta discovered that consumers describe purchases with emotional detail and unique perspectives – elements typically missing from product descriptions. The company’s Product Content Optimization platform systematically enriches entire product catalogs with consumer-centric language and attributes, creating a structured data layer that powers both frontend discovery and backend operations. Currently focused on fashion, beauty, and home decor categories, Lily AI reports that clients see double-digit increases in sales, ad impressions, and site traffic through improved product discoverability.

Vody takes a different approach, focusing on real-time search interpretation rather than catalog enrichment. The company targets enterprise retailers looking to enhance product discovery through multimodal generative AI that understands current cultural context and trending topics. "Our models understand how customers search, speak, and shop," explains CEO Stephanie Horbaczewski.

Optimizing Inventory with AI

Traditional retail operations often rely on outdated "push" models and manual processes, leading to inefficiencies in inventory management and significant waste in fresh food categories.

Nextail is tackling a fundamental disconnect in fashion retail: while consumer behavior and product lifecycles have become increasingly dynamic, inventory decisions remain largely static and intuition-based. "Despite being a multi-trillion dollar industry, fashion mostly runs on an operating model built decades ago," notes Joaquín Villalba, Nextail’s co-founder and former Head of European Logistics at Inditex.

Cognitiwe’s WeFresh platform addresses this €4 billion-plus challenge in Europe alone. The solution targets enterprise-level grocery retailers and supermarket chains where fresh food management is complex and waste reduction is a priority.

Reimagining Pricing and Promotions

Traditional approaches to pricing and promotions often rely on manual processes and broad discounting strategies that erode margins without maximizing revenue potential.

Quicklizard’s dynamic pricing platform, serving medium to large retailers managing thousands of SKUs, automates pricing for entire product catalogs. "Most retailers can only optimize 10-15% of their catalog using manual methods," explains Anat Oransky Lev, VP Marketing. The company’s open AI platform allows retailers to implement any pricing strategy through simple Python code, while machine learning modules analyze factors like price elasticity, competitor behavior, and seasonality.

RevLifter, targeting mid-market retailers, is rethinking how retailers use promotions. "Promotions have been a retail tactic for around 150 years," notes Dan Bond, VP of Marketing.

Automating Creative Content Generation with AI

The increasing demand for visual content across channels has created new bottlenecks for retailers, particularly in fashion and marketing contexts.

Fashable, serving mid-market and enterprise retailers, generates photorealistic imagery that transforms fashion industry workflows from concept to market. The platform creates AI-generated fashion imagery that remains exclusive to the brand, allowing retailers to test market response before committing to physical production while reducing sample waste and accelerating time to market.

Rocketium addresses this scaling challenge for enterprise brands advertising on social, display, and retail media platforms. Its platform automates the creation of multiple creative versions for each campaign element while predicting performance potential, eliminating the manual work of adapting content for different platforms and placements.

The Future of Retail Tech

The solutions these startups are developing signal an important shift in retail AI. While much attention has focused on consumer-facing AI applications like Amazon’s recently launched Rufus shopping assistant, these companies demonstrate how artificial intelligence can transform core retail operations. As I recently wrote, "tools like Rufus are just the beginning of how AI will reshape retail – the real transformation is happening behind the scenes."

Conclusion

For retailers evaluating where to invest in AI capabilities, these startups provide a useful framework: language optimization for discovery, intelligent inventory management, dynamic pricing and promotions, and automated content creation. Each represents an area where AI can solve specific, measurable business challenges rather than simply adding technological sophistication.

FAQs

• What are the key challenges that retail tech startups are tackling?
  • Language optimization for discovery, intelligent inventory management, dynamic pricing and promotions, and automated content creation.
• How can retailers solve the language gap between merchants and consumers?
  • Through companies like Lily AI and Vody, which are using AI to bridge the gap between product descriptions and consumer search queries.
• How can retailers optimize their inventory management?
  • Through companies like Nextail, which are using AI to transform traditional "push" models and manual processes, and Cognitiwe’s WeFresh, which is targeting fresh food inventory management.
• How can retailers reimagine pricing and promotions?
  • Through companies like Quicklizard and RevLifter, which are using AI to automate pricing and promotions, respectively.
• How can retailers automate their creative content generation?
  • Through companies like Fashable and Rocketium, which are using AI to generate photorealistic imagery and automate creative content creation, respectively.